where \(W_{\mu } \in \mathbb {R}^{D \times dim(C_m) }\) ,\(W_{\delta } \in \mathbb {R}^{D \times dim(C_m) }\)  are the learnable parameters. Other similar methods introduce the distribution as latent variable dependencies are [1]} [2]}, and our model is optimized in performance after introducing a prior distribution.
